Load torque estimation in induction motors using artificial neural networks
Autor(a) principal: | |
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Data de Publicação: | 2002 |
Outros Autores: | , , |
Tipo de documento: | Artigo de conferência |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1109/IJCNN.2002.1007717 http://hdl.handle.net/11449/35917 |
Resumo: | The induction motors are largely used in several industry sectors. The dimensioning of an induction motor has still been inaccurate because in most of the cases the load behavior in its shaft is completely unknown. The proposal of this paper is to use artificial neural networks as tool for dimensioning of induction motors rather than conventional methods, which use classical identification techniques and mechanical load modeling. Simulation results are also presented to validate the proposed approach. |
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Repositório Institucional da UNESP |
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2946 |
spelling |
Load torque estimation in induction motors using artificial neural networksThe induction motors are largely used in several industry sectors. The dimensioning of an induction motor has still been inaccurate because in most of the cases the load behavior in its shaft is completely unknown. The proposal of this paper is to use artificial neural networks as tool for dimensioning of induction motors rather than conventional methods, which use classical identification techniques and mechanical load modeling. Simulation results are also presented to validate the proposed approach.State Univ São Paulo, FE, DEE, BR-17033360 Bauru, SP, BrazilState Univ São Paulo, FE, DEE, BR-17033360 Bauru, SP, BrazilInstitute of Electrical and Electronics Engineers (IEEE)Universidade Estadual Paulista (Unesp)Goedtel, A.da Silva, I. N.Serni, PJAAvolio, E.2014-05-20T15:25:30Z2014-05-20T15:25:30Z2002-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject1379-1384http://dx.doi.org/10.1109/IJCNN.2002.1007717Proceeding of the 2002 International Joint Conference on Neural Networks, Vols 1-3. New York: IEEE, p. 1379-1384, 2002.1098-7576http://hdl.handle.net/11449/3591710.1109/IJCNN.2002.1007717WOS:000177402800246270572353521013448317899018238490000-0002-9984-9949Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengProceeding of the 2002 International Joint Conference on Neural Networks, Vols 1-3info:eu-repo/semantics/openAccess2024-06-28T13:34:43Zoai:repositorio.unesp.br:11449/35917Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T23:43:35.913775Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Load torque estimation in induction motors using artificial neural networks |
title |
Load torque estimation in induction motors using artificial neural networks |
spellingShingle |
Load torque estimation in induction motors using artificial neural networks Goedtel, A. |
title_short |
Load torque estimation in induction motors using artificial neural networks |
title_full |
Load torque estimation in induction motors using artificial neural networks |
title_fullStr |
Load torque estimation in induction motors using artificial neural networks |
title_full_unstemmed |
Load torque estimation in induction motors using artificial neural networks |
title_sort |
Load torque estimation in induction motors using artificial neural networks |
author |
Goedtel, A. |
author_facet |
Goedtel, A. da Silva, I. N. Serni, PJA Avolio, E. |
author_role |
author |
author2 |
da Silva, I. N. Serni, PJA Avolio, E. |
author2_role |
author author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (Unesp) |
dc.contributor.author.fl_str_mv |
Goedtel, A. da Silva, I. N. Serni, PJA Avolio, E. |
description |
The induction motors are largely used in several industry sectors. The dimensioning of an induction motor has still been inaccurate because in most of the cases the load behavior in its shaft is completely unknown. The proposal of this paper is to use artificial neural networks as tool for dimensioning of induction motors rather than conventional methods, which use classical identification techniques and mechanical load modeling. Simulation results are also presented to validate the proposed approach. |
publishDate |
2002 |
dc.date.none.fl_str_mv |
2002-01-01 2014-05-20T15:25:30Z 2014-05-20T15:25:30Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/conferenceObject |
format |
conferenceObject |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1109/IJCNN.2002.1007717 Proceeding of the 2002 International Joint Conference on Neural Networks, Vols 1-3. New York: IEEE, p. 1379-1384, 2002. 1098-7576 http://hdl.handle.net/11449/35917 10.1109/IJCNN.2002.1007717 WOS:000177402800246 2705723535210134 4831789901823849 0000-0002-9984-9949 |
url |
http://dx.doi.org/10.1109/IJCNN.2002.1007717 http://hdl.handle.net/11449/35917 |
identifier_str_mv |
Proceeding of the 2002 International Joint Conference on Neural Networks, Vols 1-3. New York: IEEE, p. 1379-1384, 2002. 1098-7576 10.1109/IJCNN.2002.1007717 WOS:000177402800246 2705723535210134 4831789901823849 0000-0002-9984-9949 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Proceeding of the 2002 International Joint Conference on Neural Networks, Vols 1-3 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
1379-1384 |
dc.publisher.none.fl_str_mv |
Institute of Electrical and Electronics Engineers (IEEE) |
publisher.none.fl_str_mv |
Institute of Electrical and Electronics Engineers (IEEE) |
dc.source.none.fl_str_mv |
Web of Science reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1808129547201150976 |